Volcanic rock reservoir full aperture characterization method based on LTNA and NMR of fractal theory

Abstract

The invention provides a volcanic rock reservoir full aperture characterization method based on LTNA and NMR of a fractal theory. The method comprises the following steps: S1, obtaining a pore cumulative volume percentage and T2 distribution curve of a sample in an NMR base saturation removal state; s2, acquiring a DFT model pore cumulative volume percentage and r distribution curve of LTNA; s3, on the basis of the fractal theory, obtaining a fractal equation suitable for NMR and LTNA, utilizing a pore cumulative volume percentage and T2 distribution double logarithmic curve of the NMR in a base saturation removal state and a pore cumulative volume percentage and r double logarithmic curve of the DFT model of LTNA to perform segmented calculation on fractal trend lines, obtaining a T2 value and a pore r value at a fractal threshold value, and calculating a multiple relation Z of the T2 value and the pore r value, nMR aperture time domain distribution is converted into spatial domain distribution, and a full aperture characterization method based on the fractal theory and using LTNA and NMR experiments is established. The invention provides a reliable volcanic rock reservoir full aperture characterization method, and solves the technical problems of complex pore structure and wide aperture distribution of the volcanic rock reservoir.

Description

Technical Field

[0001] The invention belongs to the technical field of full-pore characterization of unconventional reservoirs, and in particular relates to a full-pore characterization method of volcanic rock reservoirs based on LTNA and NMR analysis theory. Background Art

[0002] With the continuous growth of energy demand, the development and utilization of unconventional oil and gas resources have received more and more attention. Volcanic rock, as an important unconventional reservoir, plays an important role. In the exploration and development of unconventional oil and gas resources, the pore structure characteristics of the reservoir are the key factors that determine its storage capacity and production performance. The pore structure of volcanic reservoirs is complex and the pore size distribution is wide, which brings great challenges to the characterization of reservoirs. Traditional reservoir characterization methods often rely on a single physical or chemical means, which is difficult to fully reflect the pore characteristics of volcanic reservoirs, especially the characterization within the full pore size range. In addition, the study of the pore structure characteristics of volcanic reservoirs has always faced the limitations of technical means and the challenges of characterization accuracy.

[0003] At present, nuclear magnetic resonance (NMR) technology and nitrogen adsorption (LTNA) technology are commonly used methods for reservoir pore structure characterization. NMR is a non-destructive, fast and low-cost technology, and is currently the most promising technology for full-size pore characterization of volcanic reservoirs. NMR technology can reflect the distribution information of the relative sizes of all pores in the sample by measuring the relaxation time of hydrogen protons in rock samples. That is, NMR technology directly obtains the relationship between the signal amount and the relaxation time (time domain). The time domain needs to be converted into pore size distribution (spatial domain) to accurately reflect the distribution information of the absolute size of the pores. LTNA technology can invert the pore size distribution by measuring the adsorption amount of the sample at different relative pressures, but this technology is mainly suitable for the characterization of small and medium pores, and has limited recognition ability for large pores and fractures. At present, there is no method to economically and quickly characterize the full pore size distribution of volcanic reservoirs using a single characterization method.

[0004] In addition, existing characterization methods are often complex and cumbersome, separated from each other and have a limited scope of application. Therefore, developing a method that can comprehensively characterize the full pore size distribution of volcanic reservoirs is of great significance for improving the exploration and development efficiency of unconventional oil and gas resources. Summary of the invention

[0005] The purpose of the present invention is to solve the problem that a single pore size characterization method in the prior art is insufficient for characterizing the full pore size of a volcanic reservoir.

[0006] To achieve the above object, the present invention provides a method for characterizing the full pore size of volcanic reservoirs by LTNA and NMR based on fractal theory, the steps of which are as follows:

[0007] S1. Obtain the pore cumulative volume percentage and T of the sample NMR desaturated state 2 Distribution curve;

[0008] S101, washing and drying the rock samples of the volcanic rock reservoir to obtain dry rock samples, weighing the sample mass, and conducting the first NMR experiment to obtain the T of the dry sample NMR. 2 Distribution curve;

[0009] S102, pressurize the dry sample to saturate with n-dodecane, perform a second NMR experiment, and obtain the NMR saturation state T 2 Distribution curve;

[0010] S103, measure the pore volume, using the T of dry sample NMR 2 The distribution curve is used as the basis, and the NMR saturation state T 2 The distribution curve minus the T of the dry sample NMR 2 The distribution curve is used to obtain the pore volume increment and T of the sample per unit mass NMR desaturation state. 2 Distribution curve, pore volume accumulation, obtain the pore cumulative volume percentage and T of the sample NMR desaturated state 2 Distribution curve;

[0011] S2. Obtain the cumulative pore volume percentage and r distribution curve of the DFT model of LTNA; carry out a low-temperature LTNA experiment on the sample after the washing oil drying treatment in step S1 to obtain the LTNA adsorption isotherm and desorption isotherm; based on the density functional theory, use the DFT model to obtain the LTNA experimental pore volume increment and r distribution curve, accumulate the pore volume, and obtain the DFT model pore cumulative volume percentage and r distribution curve of LTNA;

[0012] S3. Based on fractal theory, the fractal equation applicable to NMR and LTNA is obtained; the cumulative volume percentage of pores in the desaturated state of NMR is related to T 2 The fractal trend line of the double logarithmic curve of the distribution and the DFT model of LTNA is calculated by segmentation, and the fractal threshold T is obtained. 2 The multiple relationship Z between the two is obtained by using the Z value. The pore volume increment of the NMR desaturated state is related to T 2 The distribution curve is converted into pore volume increment and full pore size distribution curve, so as to achieve the purpose of converting NMR pore size time domain distribution into space domain distribution, and establish a full pore size characterization method based on fractal theory using LTNA and NMR experiments; the details are as follows:

[0013] S301. Based on fractal theory, the cumulative volume percentage of pores in the NMR desaturated state and T2 Fractal equation and DFT model of LTNA The fractal equation of pore cumulative volume percentage and r;

[0014] S302, according to the fractal equation, the cumulative volume percentage of pores in the NMR de-basement saturation state and the relaxation time are logarithmically calculated to obtain the cumulative volume percentage of pores in the NMR de-basement saturation state and T 2 Distribution double logarithmic curve, the cumulative volume percentage of pores in the DFT model of LTNA and the r radius are logarithmically calculated to obtain the cumulative volume percentage of pores in the DFT model of LTNA and the r distribution double logarithmic curve;

[0015] S303, using NMR to remove the base saturation state of the pore cumulative volume percentage and T 2 The fractal trend line is calculated by segmenting the distribution double logarithmic curve to obtain the NMR fractal threshold;

[0016] S304, using the LTNA DFT model pore cumulative volume percentage and r distribution double logarithmic curve to segmentally calculate the fractal trend line, and obtain the LTNA fractal threshold;

[0017] S305, determine the relaxation time T at the fractal threshold 2X and pore radius r X The multiple relationship Z is used to convert the pore volume increment of the NMR desaturated state to T 2 The distribution curves were converted into pore volume increment and total pore size distribution curves.

[0018] Beneficial effects:

[0019] The present invention combines LTNA and NMR technologies, and constructs fractal equations of two experiments based on fractal theory, calculates the aperture value and relaxation time at the fractal threshold between fractal trend lines, and establishes a conversion relationship between the space domain and the time domain, thereby converting the NMR relaxation time distribution into the aperture distribution, thereby achieving the purpose of full aperture characterization. This method not only improves the accuracy of reservoir pore structure feature characterization, but also has good universality and expanded application range, and can provide effective data support for the exploration and development of unconventional oil and gas resources. In addition, the present invention also solves the technical problems of complex pore structure and wide pore size distribution of volcanic reservoirs, improves resource development efficiency and economic benefits, and conforms to the development trend of environmental friendliness and green exploration. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of the full-pore characterization method of volcanic reservoir provided by the present invention;

[0021] Figure 2 is the pore volume increment per unit mass of the NMR substrate saturation state provided by the present invention and T2 Distribution curve graph;

[0022] Figure 3 is the cumulative volume percentage of pores in the NMR de-base saturation state provided by the present invention and T 2 Distribution curve;

[0023] Figure 4 The LTNA adsorption isotherm and desorption isotherm provided by the present invention;

[0024] Figure 5 It is a DFT model pore volume increment and r distribution curve diagram of LTNA provided by the present invention;

[0025] Figure 6 is the cumulative volume percentage and r distribution curve of the DFT model pores of the LTNA provided by the present invention;

[0026] Figure 7 is the cumulative pore volume percentage of the NMR de-base saturation state provided by the present invention and T 2 Distribution double logarithmic curve;

[0027] Figure 8 It is a double logarithmic curve graph of the cumulative volume percentage of pores and r distribution of the DFT model of LTNA provided by the present invention;

[0028] Fig. 9 It is a comparison diagram of the NMR unit mass saturated state pore volume increment and r distribution curve obtained in Example 1 of the present invention and the DFT model pore volume increment and r distribution curve of LTNA;

[0029] Fig.10 is the pore volume increment of sample 2 in the NMR desaturated state and T 2 Distribution curve;

[0030] Fig.11 is the cumulative volume percentage of pores in the NMR desaturated state of sample 2 and T 2 Distribution curve;

[0031] Fig.12 It is the LTNA adsorption and desorption isotherms of sample No. 2;

[0032] Fig.13 It is the DFT model pore volume increment and r distribution curve of sample No. 2 LTNA;

[0033] Fig.14 is the DFT model pore cumulative volume percentage and r distribution curve of sample No. 2 LTNA;

[0034] Fig.15It is the double logarithmic curve of the cumulative volume percentage of pores and r distribution of the DFT model of sample LTNA No. 2;

[0035] Fig.16 is the cumulative pore volume percentage of sample 2 in the NMR desaturated state and T 2 Distribution double logarithmic curve;

[0036] Fig.17 It is a comparison diagram of the NMR unit mass saturated state pore volume increment and r distribution curve obtained in Example 2 and the DFT model pore volume increment and r distribution curve of LTNA. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0038] The application principle of the present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0039] Embodiment 1:

[0040] like Figure 1 As shown in the figure, a full pore size characterization method of volcanic reservoirs based on LTNA and NMR based on fractal theory is as follows:

[0041] S1. Obtain the pore cumulative volume percentage and T of the sample NMR desaturated state 2 Distribution curve;

[0042] S101. The rock samples of the volcanic reservoir were fully washed with acetone and dichloromethane, and dried in a vacuum drying oven at 110°C for 24 hours to obtain dry rock samples. The samples were weighed and the first NMR experiment was performed to obtain the T values ​​of the dry samples. 2 Distribution curve;

[0043] S102, the dry sample was fully saturated with n-dodecane at 10 MPa for 24 h, and a second NMR experiment was performed to obtain the NMR saturation state T 2 Distribution curve;

[0044] The measurement parameters in the two NMR experiments were set as follows: main value of RF signal frequency (SF): 12 MHz, echo time (TE): 0.15 ms, sampling frequency (SW): 250 kHz, repetition time sampling interval (TW): 4000 ms, RF delay (RFD): 0.08 ms, number of echoes (NECH): 12000, and cumulative sampling times (NS): 32.

[0045] S103. Measure the pore volume. Using the T 2 distribution curve of the dry sample NMR as the base, subtract the NMR saturation state T 2 distribution curve obtained in step S102 from the T 2 distribution curve of the dry sample NMR, so as to obtain the pore volume increment of the NMR de-based saturation state per unit mass of the sample and the T 2 distribution curve ( Figure 2 ). Cumulate the pore volume to obtain the cumulative pore volume percentage of the NMR de-based saturation state of the dry sample and the T 2 distribution curve ( Figure 3 );

[0046] S2. Obtain the cumulative pore volume percentage and r distribution curve of the DFT model of LTNA;

[0047] S201. Use the same washed sample tested in step S1 to conduct a low-temperature LTNA experiment. Grind the volcanic rock sample to a particle size of 80 mesh; and after drying at 90 °C for 1 hour, heat it at 110 °C for 10 hours to completely remove free water and volatile impurities; evacuate to remove other gas components and measure the mass of the rock sample; under the constant temperature condition of 77.35 K, using high-purity nitrogen gas (purity > 99.999%) as the adsorbate, gradually increase and decrease the relative pressure of the gas (0.009 < P / P0 < 0.995) to measure the adsorption amount and desorption amount respectively, and then obtain the LTNA adsorption isotherm and desorption isotherm ( Figure 4 ).

[0048] S202. Based on the density functional theory, use the DFT model to obtain the pore volume increment and r distribution curve of the LTNA experiment ( Figure 5 ). Cumulate the pore volume to obtain the cumulative pore volume percentage and r distribution curve of the DFT model of LTNA ( Figure 6 ).

[0049] S3. Based on the fractal theory, obtain the fractal equations applicable to NMR and LTNA. Use the double logarithmic curve of the cumulative pore volume percentage of the NMR de-based saturation state and the T 2 distribution and the double logarithmic curve of the cumulative pore volume percentage of the DFT model of LTNA and the r distribution to calculate the fractal trend line in segments respectively, obtain the T 2 value and r value at the fractal threshold, obtain the multiple relationship Z between the two. Use the Z value to convert the pore volume increment and T 2 distribution curve of the NMR de-based saturation state into the pore volume increment and full pore size distribution curve, so as to achieve the purpose of converting the NMR pore size time domain distribution into the spatial domain distribution, and establish a full pore size characterization method based on the fractal theory using LTNA and NMR experiments.

[0050] S301. Based on fractal theory, the cumulative volume percentage of pores in the NMR desaturated state and T 2 The fractal equation and the fractal equation of the cumulative volume percentage of pores in the DFT model of LTNA and r; the specific calculation process of the fractal equation of the cumulative volume percentage of pores in the DFT model of LTNA and r is as follows:

[0051] The pore number calculation equation based on fractal theory is as follows:

[0052]

[0053] in is the number of pore radii greater than r, r max is the maximum pore radius, r is the pore radius, a is the fractal factor, D is the fractal dimension, f(r) is the density function representing the pore size, and the calculation formula of f(r) is as shown in formula (2):

[0054]

[0055] Assuming that the pores are ideal spheres, the cumulative volume of pores with a radius less than r is It can be expressed as:

[0056]

[0057] where r min is the minimum pore radius, and the total pore volume V total It can be expressed as:

[0058]

[0059] The cumulative volume percentage S of pores with a radius less than r can be expressed as:

[0060]

[0061] Due to r min <<r max , formula (5) is simplified to:

[0062]

[0063] Taking the logarithm of both sides of formula (6) can obtain the fractal calculation equation of LTNA pore cumulative volume percentage and r:

[0064] lgS=(3-D)lgr-(3-D)lgr max (7)

[0065] The relationship between the cumulative volume percentage of pores and the pore size obtained by the DFT model of LTNA is applied to the LTNA fractal calculation equation by applying formula (7):

[0066] lgS LTNA =(3-D)lgr-(3-D)lgr max (8)

[0067] Where S LTNA is the cumulative volume percentage of LTNA pores.

[0068] The relationship between the cumulative volume percentage of pores in the NMR desaturated state and T 2 The specific calculation process of the fractal equation is as follows:

[0069] T 2 The influence of receptor relaxation, surface relaxation and diffusion relaxation, therefore T 2 Relaxation can be expressed as:

[0070]

[0071] Where T 2B represents volume relaxation, T 2S represents surface relaxation, T 2D represents diffusion relaxation, T 2 is the relaxation time. 2B With T 2S Ignoring the surface relaxation rate ρ 2 and surface-to-volume ratio With T 2 is proportional, so T 2 It can be expressed as:

[0072]

[0073] where F s is the geometric shape factor, r is the pore radius. For the same sample, ρ 2 and F s can be regarded as a constant, so according to formula (10) we get T 2 ∝r, and the two correspond one to one. Therefore, according to formula (7), the fractal equation of the NMR experiment is obtained:

[0074] lgS NMR =(3-D)lgT 2 -(3-D)lgT 2max (11)

[0075] Where S NMR is the cumulative volume percentage of NMR pores, T 2max is the maximum relaxation time, and D is the fractal dimension.

[0076] S302, according to the fractal equation, the NMR pore cumulative volume percentage and the relaxation time are logarithmically calculated to obtain the NMR pore cumulative volume percentage and T in the de-basement saturation state. 2 Distribution double logarithmic curve ( Figure 7 ), the cumulative volume percentage of LTNA pores and the r radius are calculated logarithmically to obtain the double logarithmic curve of the cumulative volume percentage of LTNA pores and the r distribution of the DFT model ( Figure 8 ).

[0077] S303, using NMR to remove the base saturation state of the pore cumulative volume percentage and T 2 The fractal trend line is calculated segmentally using the double logarithmic distribution curve to obtain the NMR fractal threshold. The specific process is as follows:

[0078] S3031, the rock pore structure is self-similar and the fractal value is between 2 and 3, so the cumulative pore volume percentage of the NMR desaturated state and T 2 The fractal dimension values ​​of all adjacent test sampling points in the distribution double logarithmic curve;

[0079] S3032. Select data with stable fractal dimension values ​​between 2 and 3, calculate the fractal trend line in segments, and determine the T at the fractal threshold. 2 The NMR experimental data should obtain three fractal trend lines and two fractal thresholds T 2X (at small relaxation time) and T 2Y (at large relaxation time);

[0080] S304, using the LTNA DFT model pore cumulative volume percentage and r distribution double logarithmic curve to calculate the fractal trend line in sections, and obtain the LTNA fractal threshold. The specific steps are as follows:

[0081] S3041, the rock pore structure has self-similarity and the fractal value is between 2 and 3, so the DFT model of LTNA is calculated to calculate the pore cumulative volume percentage and the fractal dimension values ​​of all adjacent test sampling points in the r distribution double logarithmic curve;

[0082] S3042. Select data with stable fractal dimension values ​​between 2 and 3, calculate the fractal trend line in segments, and determine the r value at the fractal threshold. The LTNA experiment should obtain two fractal trend lines and one fractal threshold r. X .

[0083] According to formula (8) and formula (11), fractal curves are drawn respectively, and the LTNA fractal threshold r is obtained according to the fractal curves. X and the NMR fractal threshold T 2X , according to formula (10):

[0084] r X=ZT 2X (12)

[0085] S305. Determine the relaxation time T at the fractal threshold 2X and the pore radius r X of the multiple relationship Z. According to this multiple relationship, the pore volume increment in the NMR de-based saturation state is converted into the pore volume increment and the full pore size distribution curve (spatial domain) with T 2 distribution curve (time domain), thereby establishing a full pore size characterization method based on fractal theory using LTNA and NMR experiments (such as Fig. 9 ).

[0086] Example 2:

[0087] Referring to the operation steps and operation parameters of Example 1, the reservoir sample 2# is pretreated, and NMR experiments and LTNA experiments are carried out Fig.10 is the pore volume increment in the NMR de-based saturation state of sample No. 2 and T 2 distribution curve. The curve has a three-peak characteristic. The left peak is located at 10 -1 to 10 0 ms, mainly representing the pore distribution. The middle peak is located at 10 0 to 10 1 ms, mainly representing the pore and fracture distribution. The right peak is located at 10 2 to 10 3 ms. It mainly represents the fracture distribution. The pore size distribution range of the reservoir space developed in the sample revealed by NMR is relatively wide. Fig.11 is the pore cumulative volume percentage in the NMR de-based saturation state of sample No. 2 and T 2 distribution curve. Fig.12 is the LTNA adsorption isotherm and desorption isotherm of sample No. 2. The adsorption curve of the sample can be described in three stages. The first stage is the monolayer adsorption stage. In this stage, the relative pressure is relatively low, and the adsorption curve shows a convex upward shape. There is an obvious inflection point at point B on the curve, representing the completion of the monolayer adsorption process. Monolayer adsorption is usually considered physical adsorption, involving the relatively weak van der Waals force between molecules; the second stage is the multilayer adsorption stage. In this stage, P / P0 < 0.45, and the adsorption curve is slightly convex upward. Multilayer adsorption may include physical adsorption and chemical adsorption, involving the interaction between molecules; as the relative pressure continues to increase, it enters the third stage of the curve. In this stage, capillary condensation occurs. In this stage, 0.45 < P / P0 < 0.995, and the adsorption curve rises rapidly until it approaches the saturated vapor pressure, without obvious adsorption limitation. Nitrogen liquefies to form droplets. In the desorption stage, it is also controlled by capillary condensation. The desorption curve separates from the adsorption thin line, forming a hysteresis loop, indicating that the pores in the sample are mainly open pores. Fig.13This is the DFT model pore volume increment and r distribution curve of sample No. 2 LTNA. The peak of the curve is in the range of 10-100nm, which mainly represents the distribution of pores, and the pores in the sample are mainly nano-scale pores. Fig.14 This is the DFT model pore cumulative volume percentage and r distribution curve of sample No. 2 LTNA. Fig.15 This is the double logarithmic curve of the cumulative volume percentage of pores and the r distribution of the DFT model of sample No. 2 LTNA. The curve shows an obvious two-segment type. The pore size threshold r at the inflection point of the two segments is X It is 68.499nm. Fig.16 is the cumulative pore volume percentage of sample 2 in the NMR desaturated state and T 2 The double logarithmic distribution curve shows an obvious three-segment curve, and there are two inflection point thresholds in the three-segment curve. 2X is 1.589ms and T 2Y is 13.049 ms. 2X The r of LTNA is 1.589ms and X Substituting the Z value into formula (12) is 68.499 nm, the Z value of the sample is 43.108. Substituting the Z value into the pore volume increment of the NMR desaturated state of sample No. 2 and T 2 The distribution curve of the pore volume increment and r distribution curve of the NMR de-base saturation state is obtained to achieve the full pore size characterization of the sample. Fig.17 It is a comparison diagram of the NMR unit mass saturated state pore volume increment and r distribution curve obtained in Example 2 and the DFT model pore volume increment and r distribution curve of LTNA. The consistency of the peak position and peak size of the two curves in this figure shows the rationality of the present application.

[0088] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A full-pore characterization method for volcanic reservoirs based on LTNA and NMR based on fractal theory, characterized in that: Here are the steps: S1, obtaining the pore cumulative volume percentage and T2 distribution curve of the sample NMR de-basement saturation state; S101, washing and drying the rock samples of the volcanic rock reservoir to obtain dry rock samples, weighing the samples, performing the first NMR experiment, and obtaining the T2 distribution curve of the dry sample NMR; S102, pressurizing the dry sample to saturate with n-dodecane, performing a second NMR experiment, and obtaining a T2 distribution curve of the NMR saturation state; S103, measuring the pore volume, taking the T2 distribution curve of the dry sample NMR as the base, subtracting the T2 distribution curve of the dry sample NMR from the obtained T2 distribution curve of the NMR saturation state, thereby obtaining the pore volume increment and T2 distribution curve of the sample unit mass NMR de-base saturation state, accumulating the pore volume, and obtaining the pore cumulative volume percentage and T2 distribution curve of the sample NMR de-base saturation state; S2. Obtain the cumulative pore volume percentage and r distribution curve of the DFT model of LTNA; carry out a low-temperature LTNA experiment on the sample after the washing oil drying treatment in step S1 to obtain the LTNA adsorption isotherm and desorption isotherm; based on the density functional theory, use the DFT model to obtain the LTNA experimental pore volume increment and r distribution curve, accumulate the pore volume, and obtain the DFT model pore cumulative volume percentage and r distribution curve of LTNA; S3. Based on fractal theory, a fractal equation applicable to NMR and LTNA is obtained; the double logarithmic curve of the cumulative volume percentage of pores and T2 distribution in the NMR de-base saturation state and the double logarithmic curve of the DFT model of pores and r distribution in the LTNA are used to calculate the fractal trend line in sections, and the T2 value and r value at the fractal threshold are obtained, and the multiple relationship Z between the two is obtained. Using the Z value, the pore volume increment and T2 distribution curve of the NMR de-base saturation state are converted into the pore volume increment and full pore size distribution curve, so as to achieve the purpose of converting the NMR pore size time domain distribution into the space domain distribution, and establish a full pore size characterization method based on fractal theory using LTNA and NMR experiments; the details are as follows: S301. Based on the fractal theory, the pore cumulative volume percentage and T2 fractal equation of the NMR desaturated state and the fractal equation of the pore cumulative volume percentage and r of the DFT model of LTNA are obtained; S302, according to the fractal equation, logarithmically calculate the cumulative volume percentage of pores in the NMR de-basement saturation state and the relaxation time to obtain a double logarithmic curve of the cumulative volume percentage of pores in the NMR de-basement saturation state and T2 distribution, and logarithmically calculate the cumulative volume percentage of pores in the DFT model of LTNA and the r radius to obtain a double logarithmic curve of the cumulative volume percentage of pores in the DFT model of LTNA and r distribution; S303, calculating the fractal trend line by segmentation using the pore cumulative volume percentage of the NMR de-basement saturation state and the T2 distribution double logarithmic curve to obtain the NMR fractal threshold; S304, using the LTNA DFT model pore cumulative volume percentage and r distribution double logarithmic curve to segmentally calculate the fractal trend line, and obtain the LTNA fractal threshold; S305, determine the relaxation time T at the fractal threshold 2X and pore radius r X The multiple relationship Z is used to convert the pore volume increment and T2 distribution curve of the NMR de-base saturation state into the pore volume increment and total pore size distribution curve.

2. The full-pore characterization method of volcanic reservoirs based on LTNA and NMR of fractal theory according to claim 1 is characterized in that: In step S101, the rock sample is subjected to an oil washing and drying treatment using acetone and dichloromethane, and then dried in a vacuum drying oven at 110° C. for 24 hours.

3. The full-pore characterization method of volcanic reservoirs based on LTNA and NMR of fractal theory according to claim 1, characterized in that: The step S102 of subjecting the dry sample to pressurized saturated n-dodecane treatment includes fully saturating the sample with n-dodecane at 10 MPa for 24 hours.

4. The method for full-pore characterization of volcanic reservoirs based on LTNA and NMR of fractal theory according to claim 1, characterized in that: The measurement parameters of the NMR experiment in step S101 and step S102 are: main value of RF signal frequency: 12 MHz, echo time: 0.15 ms, sampling frequency: 250 kHz, repetition time sampling interval: 4000 ms, RF delay: 0.08 ms, number of echoes: 12000, and cumulative sampling times:

32.

5. The method for full-pore characterization of volcanic reservoirs based on LTNA and NMR of fractal theory according to claim 1, characterized in that: In step S2, low-temperature LTNA test: the volcanic rock is ground to a particle size of 80 mesh; after drying at 90°C for 1 hour, it is heated at 110°C for 10 hours to completely remove free water and volatile impurities; vacuum is evacuated to remove other gas components and the mass of the rock sample is measured; at a constant temperature of 77.35K, nitrogen with a purity of >99.999% is used as the adsorbent, and the relative pressure of the gas is gradually increased and decreased to measure the adsorption amount and desorption amount, respectively, and then the LTNA adsorption isotherm and desorption isotherm are obtained.

6. The method for full-pore characterization of volcanic reservoirs based on LTNA and NMR of fractal theory according to claim 1, characterized in that: The specific calculation process of the fractal equation of the pore cumulative volume percentage and r of the DFT model of LTNA in step S301 is as follows: The pore number calculation equation based on fractal theory is: in is the number of pore radii greater than r, r max is the maximum pore radius, r is the pore radius, a is the fractal factor, D is the fractal dimension, f(r) is the density function representing the pore size, and the calculation formula of f(r) is: Assuming that the pores are ideal spheres, the cumulative volume of pores with a radius less than r is It is expressed as: where r min is the minimum pore radius, and the total pore volume V total It is expressed as: The cumulative volume percentage S of pores with a radius less than r can be expressed as: Due to r min <<r max , formula (5) is simplified to: Taking the logarithm of both sides of formula (6) can obtain the fractal calculation equation of LTNA pore cumulative volume percentage and r: lgS=(3-D)lgr-(3-D)lgr max (7) The relationship between the cumulative volume percentage of pores and r obtained by the DFT model of LTNA is obtained by applying formula (7) to obtain the LTNA fractal calculation equation: lgS LTNA =(3-D)lgr-(3-D)lgr max (8) Where S LTNA is the cumulative percentage of LTNA pores.

7. The method for full-pore characterization of volcanic reservoirs based on LTNA and NMR of fractal theory according to claim 1, characterized in that: The cumulative volume percentage of pores in the NMR desaturated state and the T2 fractal equation in step S301 are calculated as follows: T2 is affected by receptor relaxation, surface relaxation and diffusion relaxation, so T2 is expressed as: Where T 2B represents volume relaxation, T 2S represents surface relaxation, T 2D represents diffusion relaxation, T2 is the relaxation time; T 2B With T 2S Ignoring the surface relaxation rate ρ2 and the surface-to-volume ratio It is proportional to T2, so T2 is expressed as: Among them, F s is the geometric shape factor, r is the pore radius, and T2 is the relaxation time; for the same sample, ρ2 and F s can be regarded as a constant, so according to formula (10), we get T2∝r, and the two correspond one to one; therefore, according to formula (7), we get the fractal equation of the NMR experiment: lgS NMR =(3-D)lgT2-(3-D)lgT 2max (11) Where S NMR is the cumulative volume percentage of NMR pores, T 2max is the maximum relaxation time, and D is the fractal dimension.

8. The method for full-pore characterization of volcanic reservoirs based on LTNA and NMR of fractal theory according to claim 1, characterized in that: The specific process of calculating the NMR fractal threshold in step S303 is as follows: S3031, the rock pore structure has self-similarity and the fractal value is between 2 and 3, so the cumulative pore volume percentage of the NMR de-basement saturation state and the fractal dimension values ​​of all adjacent test sampling points in the T2 distribution curve are calculated; S3032. Select data with stable fractal dimension values ​​between 2 and 3, calculate the fractal trend line in segments, and determine the T2 value at the fractal threshold. The NMR experiment should obtain three fractal trend lines and two fractal thresholds T 2X and T 2Y .

9. The method for full-pore characterization of volcanic reservoirs based on LTNA and NMR of fractal theory according to claim 1, characterized in that: The specific process of calculating the LTNA fractal threshold in step S304 is as follows: S3041, the rock pore structure has self-similarity and the fractal value is between 2 and 3, so the DFT model of LTNA is calculated to calculate the pore cumulative volume percentage and the fractal dimension values ​​of all adjacent test sampling points in the r distribution double logarithmic curve; S3042. Select data with stable fractal dimension values ​​between 2 and 3, calculate the fractal trend line in segments, and determine the r value at the fractal threshold. The LTNA experiment should obtain two fractal trend lines and one fractal threshold r. X ; According to formula (8) and formula (11), fractal curves are drawn respectively, and the LTNA fractal threshold r is obtained by using the fractal curves. X and the NMR fractal threshold T 2X , obtained according to formula (10). r X =ZT 2X (12)。

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